apeforest commented on a change in pull request #13614: Make to_tensor and
normalize to accept 3D or 4D tensor inputs
URL: https://github.com/apache/incubator-mxnet/pull/13614#discussion_r241114949
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File path: python/mxnet/gluon/data/vision/transforms.py
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@@ -154,10 +157,29 @@ class Normalize(HybridBlock):
Inputs:
- - **data**: input tensor with (C x H x W) shape.
+ - **data**: input tensor with (C x H x W) or (N x C x H x W) shape.
Outputs:
- **out**: output tensor with the shape as `data`.
+
+ Examples
+ --------
+ >>> transformer = transforms.Normalize(mean=(0, 1, 2), std=(3, 2, 1))
+ >>> image = mx.nd.random.uniform(0, 1, (3, 4, 2))
Review comment:
Can you give an example of 4D (N x C x H x W) here?
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